Evidence map›Paper›PMID 37439331›Full record

ArticleNucleic acids research2023

iSMOD: an integrative browser for image-based single-cell multi-omics data.

Weihang Zhang, Jinli Suo, Yan Yan, Runzhao Yang, Yiming Lu, Yiqi Jin, Shuochen Gao, Shao Li, Juntao Gao, Michael Zhang and 1 more

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 33% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 3 institutions in 2 countries.

Weihang ZhangDepartment of Automation, Tsinghua University, Beijing 100084, China.ORCID 0000-0003-3717-9473
Jinli SuoDepartment of Automation, Tsinghua University, Beijing 100084, China.
Yan YanMOE Key Laboratory of Bioinformatics; Bioinformatics Division, BNRist; Center for Synthetic & Systems Biology, Tsinghua University, Beijing 100084, China.
Runzhao YangDepartment of Automation, Tsinghua University, Beijing 100084, China.
Yiming LuDepartment of Automation, Tsinghua University, Beijing 100084, China.
Yiqi JinDepartment of Automation, Tsinghua University, Beijing 100084, China.
Shuochen GaoDepartment of Automation, Tsinghua University, Beijing 100084, China.
Shao LiDepartment of Automation, Tsinghua University, Beijing 100084, China.ORCID 0000-0002-8709-9167
Juntao GaoMOE Key Laboratory of Bioinformatics; Bioinformatics Division, BNRist; Center for Synthetic & Systems Biology, Tsinghua University, Beijing 100084, China.
Michael ZhangMOE Key Laboratory of Bioinformatics; Bioinformatics Division, BNRist; Center for Synthetic & Systems Biology, Tsinghua University, Beijing 100084, China.
Qionghai DaiDepartment of Automation, Tsinghua University, Beijing 100084, China.
Tsinghua University · CNInstitute of Bioinformatics · INBeijing Academy of Artificial Intelligence · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genomic and transcriptomic image data, represented by DNA and RNA fluorescence in situ hybridization (FISH), respectively, together with proteomic data, particularly that related to nuclear proteins, can help elucidate gene regulation in relation to the spatial positions of chromatins, messenger RNAs, and key proteins. However, methods for image-based multi-omics data collection and analysis are lacking. To this end, we aimed to develop the first integrative browser called iSMOD (image-based Single-cell Multi-omics Database) to collect and browse comprehensive FISH and nucleus proteomics data based on the title, abstract, and related experimental figures, which integrates multi-omics studies focusing on the key players in the cell nucleus from 20 000+ (still growing) published papers. We have also provided several exemplar demonstrations to show iSMOD's wide applications-profiling multi-omics research to reveal the molecular target for diseases; exploring the working mechanism behind biological phenomena using multi-omics interactions, and integrating the 3D multi-omics data in a virtual cell nucleus. iSMOD is a cornerstone for delineating a global view of relevant research to enable the integration of scattered data and thus provides new insights regarding the missing components of molecular pathway mechanisms and facilitates improved and efficient scientific research.

Indexed as

MultiomicsProteomicsGene Expression ProfilingGenomicsIn Situ Hybridization, Fluorescence

Identifiers

PMID37439331
PMCPMC10484677
OpenAlexW4384119489

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.